From Artificial Evolution to Artificial Life
Created by W.Langdon from
gp-bibliography.bib Revision:1.7906
- @PhdThesis{TJTaylor:thesis,
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author = "Timothy John Taylor",
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title = "From Artificial Evolution to Artificial Life",
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school = "Division of Informatics, University of Edinburgh",
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year = "1999",
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address = "UK",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://homepages.inf.ed.ac.uk/timt/papers/thesis/",
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URL = "http://homepages.inf.ed.ac.uk/timt/papers/thesis/thesis.ps.gz",
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URL = "http://homepages.inf.ed.ac.uk/timt/papers/thesis/thesis.pdf",
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URL = "http://www.tim-taylor.com/papers/thesis/",
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size = "317 pages",
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abstract = "This work addresses the question: What are the basic
design considerations for creating a synthetic model of
the evolution of living systems (i.e. an `artificial
life' system)? It can also be viewed as an attempt to
elucidate the logical structure (in a very general
sense) of biological evolution. However, with no
adequate definition of life, the experimental portion
of the work concentrates on more specific issues, and
primarily on the issue of open-ended evolution. An
artificial evolutionary system called Cosmos, which
provides a virtual operating system capable of
simulating the parallel processing and evolution of a
population of several thousand self-reproducing
computer programs, is introduced. Cosmos is related to
Ray's established Tierra system, but there are a number
of significant differences. A wide variety of
experiments with Cosmos, which were designed to
investigate its evolutionary dynamics, are reported. An
analysis of the results is presented, with particular
attention given to the role of contingency in
determining the outcome of the runs. The results of
this work, and consideration of the existing literature
on artificial evolutionary systems, leads to the
conclusion that artificial life models such as this are
lacking on a number of theoretical and methodological
grounds. It is emphasised that explicit theoretical
considerations should guide the design of such models,
if they are to be of scientific value. An analysis of
various issues relating to self-reproduction,
especially in the context of evolution, is presented,
including some extensions to von Neumann's analysis of
self-reproduction. This suggests ways in which the
evolutionary potential of such models might be
improved. In particular, a shift of focus is
recommended towards a more careful consideration of the
phenotypic capabilities of the reproducing individuals.
Phenotypic capabilities fundamentally involve
interactions with the environment (both abiotic and
biotic), and it is further argued that the theoretical
grounding upon which these models should be based must
include consideration of the kind of environments and
the kind of interactions required for open-ended
evolution. A number of useful future research
directions are identified. Finally, the relevance of
such work to the original goal of modelling the
evolution of living systems (as opposed to the more
general goal of modelling open-ended evolution) is
discussed. It is suggested that the study of open-ended
evolution can lead us to a better understanding of the
essential properties of life, but only if the questions
being asked in these studies are phrased
appropriately.",
- }
Genetic Programming entries for
Tim Taylor
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